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[en] Efforts to integrate the CONTAIN-LMR sodium physics and chemistry models into MELCOR 2.1 and CONTAIN 2 are in progress. Testing and results from this implementation of sodium properties are given here. The CONTAIN-LMR code was derived from an early version of the CONTAIN code and many physical models that were developed since this early version of CONTAIN are not captured by this early code version. Therefore, CONTAIN 2 is being updated with the sodium models in CONTAIN-LMR in order to facilitate verification of these models with the MELCOR code. Although CONTAIN 2, which represents the latest development of CONTAIN, now contains many of the sodium specific models, this work is not complete due to challenges from the lower cell architecture in CONTAIN 2, which is different from CONTAIN-LMR. This implementation should be completed in the coming year while sodium models from CONTAIN-LMR are integrated into MELCOR. Both spray fire and pool fire models from CONTAIN-LMR have been implemented into MELCOR. In the coming year, the atmosphere chemistry and sodium-concrete interaction models from CONTAIN-LMR will be finished. For testing, CONTAIN decks have been developed to verify and validate the models. Regarding implementing the sodium models into MELCOR, a new sodium chemistry package (called NAC) was created. Both spray fire and pool fire models from CONTAIN-LMR have been implemented and implementation of the atmosphere chemistry model from CONTAIN-LMR has begun. ABCOVE AB-5, a spray fire experiment input deck, was created to test MELCOR. An input deck for testing the pool fire chemistry model is also being developed. The available results of the validations from these two models, including a code-to-code comparison with CONTAIN-LMR are provided here. (author)
[en] CONTAIN-LMR sodium physics and chemistry models are being integrated into MELCOR 2.1 and CONTAIN 2. This report provides the testing and results from the implemented sodium properties. The CONTAIN-LMR code was derived from an early version of the CONTAIN code. Many physical models that were developed since the early version of CONTAIN are not captured by the early CONTAIN code version. Because of this, CONTAIN 2 is being updated with the CONTAIN-LMR sodium models in order to verify these sodium models with the MELCOR code. CONTAIN 2 now contains many of the sodium specific models. Challenges from the lower cell architecture in CONTAIN 2 (which is different from CONTAIN-LMR) have delayed the implementation of some sodium specific models. The remaining models should be integrated within the next year during the integration of sodium models from CONTAIN-LMR into MELCOR. CONTAIN-LMR’s spray fire and pool fire models have been implemented into MELCOR. In the coming year, the atmosphere chemistry and sodium-concrete interaction models from CONTAIN-LMR will be finished. For testing, CONTAIN decks have been developed to verify and validate the models. To implement the sodium models into MELCOR, a new sodium chemistry package (called NAC) was created. CONTAIN-LMR spray fire and pool fire models have been implemented into MELCOR 2.1. The atmosphere chemistry model from CONTAIN-LMR has begun to be implemented into MELCOR 2.1. ABCOVE AB-5, a spray fire experiment input deck, was created to test MELCOR. An input deck for testing the pool fire chemistry model is also being developed. The available results of the validations from these two models, including a code-to-code comparison with CONTAIN-LMR are provided here. (author)
[en] This report was written as part of a United States Department of Energy (DOE), Office of Nuclear Energy, Advanced Reactor Technologies program funded project to re-create the capabilities of the legacy Centralized Reliability Database Organization (CREDO) database. The CREDO database provided a record of component design and performance documentation across various systems that used sodium as a working fluid. Regaining this capability will allow the DOE complex and the domestic sodium reactor industry to better understand how previous systems were designed and built for use in improving the design and operations of future loops. The contents of this report include: overview of the current state of domestic sodium reliability databases; summary of the ongoing effort to improve, understand, and process the CREDO information; summary of the initial efforts to develop a unified sodium reliability database called the Sodium System Component Reliability Database (NaSCoRD); and explain both how potential users can access the domestic sodium reliability databases and the type of information that can be accessed from these databases.
[en] In order to investigate the effect of sodium combustion, Sandia National Laboratories (SNL) and Japan Atomic Energy Agency (JAEA) have exchanged information of sodium combustion modelling and related experimental data in the framework of Civil Nuclear Energy Research and Development Working Group (CNWG). This collaboration includes a benchmark analysis of the SNL Surtsey spray combustion experiment (SNL T3/T4 experiments) using AQUA-SF and SPHINCS in JAEA and CONTAIN-LMR in SNL. AQUA-SF is a multi-dimensional sodium combustion analysis code, and zone model (lumped mass model) is applied both in SPHINCS and CONTAIN-LMR codes for fast calculation. The benchmark analysis of the SNL T3 sodium spray combustion experiment and sensitivity study have been carried out using the AQUA-SF code in this paper. The sensitivity analysis clarifies the influencing factors of the multi-dimensional analysis such as turbulence models, radiation heat transfer model from sodium droplets, and momentum exchange between gas and droplets. Furthermore, gas temperature and oxygen concentration normalized by spray burning rate are checked in order to study the effect of local gas temperature increase at the spray burning area. The result shows that the turbulence effect and radiation from droplets, and gas temperature increase under the sodium inlet affect sodium spray burning rate significantly. (author)
[en] Accident management is an important component to maintaining risk at acceptable levels for all complex systems, such as nuclear power plants. With the introduction of passive, or inherently safe, reactor designs the focus has shifted from management by operators to allowing the system's design to take advantage of natural phenomena to manage the accident. Inherently and passively safe designs are laudable, but nonetheless extreme boundary conditions can interfere with the design attributes which facilitate inherent safety, thus resulting in unanticipated and undesirable end states. This report examines an inherently safe and small sodium fast reactor experiencing a variety of beyond design basis events with the intent of exploring the utility of a Dynamic Bayesian Network to infer the state of the reactor to inform the operator's corrective actions. These inferences also serve to identify the instruments most critical to informing an operator's actions as candidates for hardening against radiation and other extreme environmental conditions that may exist in an accident. This reduction in uncertainty serves to inform ongoing discussions of how small sodium reactors would be licensed and may serve to reduce regulatory risk and cost for such reactors.
[en] This report proposes potential research priorities for the Department of Energy (DOE) with the intent of improving the licensability of the Sodium Fast Reactor (SFR). In support of this project, five panels were tasked with identifying potential safety-related gaps in available information, data, and models needed to support the licensing of a SFR. The areas examined were sodium technology, accident sequences and initiators, source term characterization, codes and methods, and fuels and materials. It is the intent of this report to utilize a structured and transparent process that incorporates feedback from all interested stakeholders to suggest future funding priorities for the SFR research and development. While numerous gaps were identified, two cross-cutting gaps related to knowledge preservation were agreed upon by all panels and should be addressed in the near future. The first gap is a need to re-evaluate the current procedures for removing the Applied Technology designation from old documents. The second cross-cutting gap is the need for a robust Knowledge Management and Preservation system in all SFR research areas. Closure of these and the other identified gaps will require both a reprioritization of funding within DOE as well as a re-evaluation of existing bureaucratic procedures within the DOE associated with Applied Technology and Knowledge Management.
[en] The consequences of a transient in an advanced sodium-cooled fast reactor are difficult to capture with the traditional approach to probabilistic risk assessment (PRA). Numerous safety-relevant systems are passive and may have operational states that cannot be represented by binary success or failure. In addition, the specific order and timing of events may be crucial which necessitates the use of dynamic PRA tools such as ADAPT. The modifications to the SAS4A/SASSYS-1 sodium-cooled fast reactor safety analysis code for linking it to ADAPT to perform a dynamic PRA are described. A test case is used to demonstrate the linking process and to illustrate the type of insights that may be gained with this process. Finally, newly-developed dynamic importance measures are used to assess the significance of reactor parameters/constituents on calculated consequences of initiating events.
[en] This study explores the viability of using counterfactual reasoning for impact analyses when understanding and responding to “beyond-design-basis” nuclear power plant accidents. Currently, when a severe nuclear power plant accident occurs, plant operators rely on Severe Accident Management Guidelines. However, the current guidelines are limited in scope and depth: for certain types of accidents, plant operators would have to work to mitigate the damage with limited experience and guidance for the particular situation. We aim to fill the need for comprehensive accident support by using a dynamic Bayesian network to aid in the diagnosis of a nuclear reactor’s state and to analyze the impact of possible response measures.
[en] An expert panel was assembled to identify gaps in fuels and materials research prior to licensing sodium cooled fast reactor (SFR) design. The expert panel considered both metal and oxide fuels, various cladding and duct materials, structural materials, fuel performance codes, fabrication capability and records, and transient behavior of fuel types. A methodology was developed to rate the relative importance of phenomena and properties both as to importance to a regulatory body and the maturity of the technology base. The technology base for fuels and cladding was divided into three regimes: information of high maturity under conservative operating conditions, information of low maturity under more aggressive operating conditions, and future design expectations where meager data exist.